Group 11: Analysis of Prostate Cancer Data
Note ALWAYS WORK ON YOUR CHUNK TO AVOID CONFLICTS
Introduction
Our analysis exploits data from a randomised clinical trial by Byar & Greene that compares treatment of patients with prostate cancer in stages 3 and 4. Treatment consisted of different doses of diethylstilbestrol (DES). Our aim is to investigate correlations, trends, or predictive models related to prostate cancer and patient outcomes. Data are publicly available in : https://hbiostat.org/data/repo/prostate.xls
Materials and Methods {.centered} (ALEX)
The initial dataset contains information related to 502 observations of patients with prostate cancer across 18 variables. These variables encompass diverse information including patient demographics, medical history, treatment received, and health status.
The raw data were: + loaded, + cleaned
+ augmented + described + modelled. and the process of arriving at results is done in a reproducible manner.
Tidy data
- For instance we separate “rx” into three columns; “Treatment regime”, “mg” and “Drug”
![]()
Logistic Regression Modeling
The objective is to predict dosage based on the bm, weight index, primary lesion size and age adjusted haemoglobin for patients with 3 and 4 prostate cancer stage respectivelly. The coefficients of the above predictors are showed below as well as their significance as indicated by their p.values.
